Gene Transfer to Subdermal Tissues via a New Gene Gun Design
Bibliographic record
Abstract
Although particle-mediated gene transfer technology (gene gun) has been applied for gene transfer to external tissues, the application of this technology to other tissues has met with limited success. Here we report the development of a new design of a gene gun that uses helium discharge to propel DNA-coated gold beads that are suspended in liquid. Higher discharge pressures allow for the delivery of DNA to deeper tissues. Using the new gene gun to deliver a luciferase expression plasmid resulted in higher levels of gene expression in the skin than observed with conventional guns, as well as in subdermal tissues, including subcutaneous tumors. Even when using as little as 125 ng of DNA, gene expression in skin and muscle reached its peak level at 24 hr postbombardment and remained for at least 1 week. The use of a LacZ expression plasmid showed that gene expression was distributed throughout the skin with no observable pathology. The new gene gun was used to deliver a model tumor rejection antigen (a modified human papilloma virus [HPV] E7 gene) to mice. All of the treated animals developed protective immunity against HPV-positive tumors. These results demonstrate that our new design can be used in standard gene gun applications and extends the reach of gene gun technology to tissues that were previously unavailable.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".